Uncovering New Biomarkers for Prostate Cancer through Proteomic and Network Analysis

Background: Prostate cancer (PCa) is the second most prevalent solid tumor among men globally and the leading non-skin cancer in American men. In 2020 alone, approximately 1.4 million new cases of prostate cancer were diagnosed worldwide, representing 14.1% of all new cancer cases in men. This multifactorial disease exhibits substantial variation in incidence and mortality across different ethnic groups and geographic regions. Although prostate-specific antigen (PSA) remains widely used as a biomarker for PCa, its limitations reduce its effectiveness for accurate detection. Consequently, finding biomarkers that can either complement or replace PSA is a major goal in PCa research. Methods: Urine samples were collected from healthy individuals (n=5) and patients with low- and high-risk PCa (4 and 7 subjects, respectively) and were analyzed using proteomic data-derived systems biology approaches. The most promising potential biomarkers were further investigated using The Cancer Genome Atlas (TCGA) database to assess their associations with clinical and histopathological characteristics in a larger in silico patient population. Results: In addition to describing the variations of the urinary proteome, the integration of protein profiles, network models and TCGA database has highlighted new potential biomarkers, including CPM, KRT8, ITIH2 and RCN1 that could enhance PCa management. Conclusions: Our findings support the technical feasibility of this combined approach for biomarker discovery and suggest further investigation into specific urinary proteins as potential novel biomarkers in larger patient cohorts.